RRPP: Linear Model Evaluation with Randomized Residuals in a Permutation Procedure

Linear model calculations are made for many random versions of data. Using residual randomization in a permutation procedure, sums of squares are calculated over many permutations to generate empirical probability distributions for evaluating model effects. This packaged is described by Collyer & Adams (2018). Additionally, coefficients, statistics, fitted values, and residuals generated over many permutations can be used for various procedures including pairwise tests, prediction, classification, and model comparison. This package should provide most tools one could need for the analysis of high-dimensional data, especially in ecology and evolutionary biology, but certainly other fields, as well.

Version: 1.3.0
Depends: R (≥ 3.5.0)
Imports: parallel, ape, ggplot2, Matrix
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0), dplyr, tibble
Published: 2022-06-21
Author: Michael Collyer ORCID iD [aut, cre], Dean Adams ORCID iD [aut]
Maintainer: Michael Collyer <mlcollyer at gmail.com>
License: GPL (≥ 3)
URL: https://github.com/mlcollyer/RRPP
NeedsCompilation: no
Citation: RRPP citation info
Materials: README NEWS
CRAN checks: RRPP results

Documentation:

Reference manual: RRPP.pdf
Vignettes: ANOVA versus MANOVA in RRPP
Using RRPP

Downloads:

Package source: RRPP_1.3.0.tar.gz
Windows binaries: r-devel: RRPP_1.3.0.zip, r-release: RRPP_1.3.0.zip, r-oldrel: RRPP_1.3.0.zip
macOS binaries: r-release (arm64): RRPP_1.3.0.tgz, r-oldrel (arm64): RRPP_1.3.0.tgz, r-release (x86_64): RRPP_1.3.0.tgz, r-oldrel (x86_64): RRPP_1.3.0.tgz
Old sources: RRPP archive

Reverse dependencies:

Reverse depends: geomorph

Linking:

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